Critical Micelle Concentration

Abstract

The goal of this study is to determine how H2O and HDO measurements inwater vapor can be used to detect and diagnose biases in therepresentation of processes controlling tropospheric humidity inatmospheric general circulation models (GCMs). We analyze a large numberof isotopic data sets (four satellite, sixteen ground-basedremote-sensing, five surface in situ and three aircraft data sets) thatare sensitive to different altitudes throughout the free troposphere.Despite significant differences between data sets, we identify someobserved HDO/H2O characteristics that are robust across data sets andthat can be used to evaluate models. We evaluate the isotopic GCM LMDZ,accounting for the effects of spatiotemporal sampling and instrumentsensitivity. We find that LMDZ reproduces the spatial patterns in thelower and mid troposphere remarkably well. However, it underestimatesthe amplitude of seasonal variations in isotopic composition at alllevels in the subtropics and in midlatitudes, and this bias isconsistent across all data sets. LMDZ also underestimates the observedmeridional isotopic gradient and the contrast between dry and convectivetropical regions compared to satellite data sets. Comparison with sixother isotope-enabled GCMs from the SWING2 project shows that biasesexhibited by LMDZ are common to all models. The SWING2 GCMs show a verylarge spread in isotopic behavior that is not obviously related to thatof humidity, suggesting water vapor isotopic measurements could be usedto expose model shortcomings. In a companion paper, the isotopicdifferences between models are interpreted in terms of biases in therepresentation of processes controlling humidity.